Title

Survey On Various Control Techniques In Micro Grinding Processes

Keywords

Adaptive control; Artificial intelligence; Expert system; Fuzzy logic; Grinding; Neural network; Robust control; System online identification

Abstract

Due to the highly demanding geometric accuracy and surface finish for many modern products, grinding processes have been extensively used in manufacturing industry. However, it is also well accepted that grinding is one of the most complicated machining processes due to the high non-linearities, intrinsic uncertainties and time-varying characteristics. Multiple challenging problems exist in the process that limits its overall quality and production in practice. With the increasing demands for higher part geometry accuracy, better surface integrity, more productivity and other desired product parameters (e.g., minimisation of subsurface micro-damage) with less operator intervention, various control methods have been studied and implemented to control position, velocity, force, power, temperature and the material removal rate (MRR) during the grinding process, in order to achieve the desired system performance within certain cost/time. This paper reviews different control strategies in order to provide a guideline for academic researchers and industrial practitioners in improving the final product quality with increased possible process flexibility. Copyright © 2009, Inderscience Publishers.

Publication Date

1-1-2009

Publication Title

International Journal of Nanomanufacturing

Volume

3

Issue

4

Number of Pages

398-408

Document Type

Review

Personal Identifier

scopus

DOI Link

https://doi.org/10.1504/IJNM.2009.027503

Socpus ID

68649101216 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/68649101216

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